Biological phenomena related to cell rolling and arrest, such as the motion signatures of neutrophils over the endothelial lining, have been studied extensively. Transient bond formation and breakage between sialyl-lewisx groups (receptors) on neutrophils and selectins (ligands) on the endothelium cause the neutrophils to move slowly over the interior of the blood vessel. This results in the engagement of integrins that arrest neutrophil motion. This behavior has been reproduced in vitro by employing selectin-functionalized microparticles, a model that relies on specific interactions between biomolecules. Our work is focused on understanding and mimicking such phenomena by reproducing the motion signatures of skipping, rolling, and arrest in an entirely non-biological system based on colloidal interactions with a surface bearing randomly distributed polymeric nanoconstructs on a repulsive background field.

A novel and predictive computational model is validated through extensive comparisons to experiment for the non-biological system. This model is then used to interpret experimental results by providing detailed insight into the comparative influence of each of various functional parameters: ionic strength, particle size, nanoconstruct length scales, shear rate, etc. The model combines hydrodynamic forces and torques exerted by the fluid flow to the heterogeneous colloidal landscape presented by the nanopatterned surface to simulate particle motion. Frictional forces are incorporated upon contact with the surface, giving rise to the motion signatures of rolling, skipping and firm adhesion.

Simulation of particle dynamics using the model yields predictions of adhesion thresholds that are in excellent quantitative agreement with experimental data. Multi-variable phase-space maps, or “adhesion state diagrams,” demarcate the regimes of different motion signatures (no contact, rolling, skipping, arrest) over a range of parameter space. Comparison of these phase-space maps with the state diagrams for neutrophil rolling reveals qualitative agreement in the structure of the diagrams along with similar quantitative trends, thereby further establishing the relevance of this work to understanding biomimetic behavior. Comparisons of characteristic nanoconstruct density, the distribution of particle rolling velocities, and the mean force and energy per nanoconstruct are made with analogous parameters in biological systems for different conditions of particle adhesion. This work explores how systems can be designed so that biomimetic particles exhibit similar dynamic motion signatures to neutrophils. Extensions are made to particle-surface interactions governed by both colloidal forces from a heterogeneous surface and physical bonds between ligands and receptors.